Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 848 83 909 966 961 470 318 343 37 360 750 484 594 342 722 429 312 143 804 886
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 429 342 848 83 886 484 312 909 470 NA 37 722 750 360 594 961 143 343 966 NA NA 318 804
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 5 4 2 1 4 3 1 5 4 1
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "s" "c" "j" "g" "h" "H" "T" "A" "R" "N"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 3 4 5
which( manyNumbersWithNA > 900 )
[1] 8 16 19
which( is.na( manyNumbersWithNA ) )
[1] 10 20 21
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 909 966 961
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 909 966 961
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 909 966 961
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "H" "T" "A" "R" "N"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "s" "c" "j" "g" "h"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE FALSE FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 6 7 8 10 12 13 14 16 17
sum( manyNumbers %in% 300:600 )
[1] 9
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "small" "large" "small" "large" "small" "small" "large" "small" NA "small" "large" "large" "small" "large" "large" "small" "small" "large" NA
[21] NA "small" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "small" "large" "small" "large" "small" "small" "large" "small" "UNKNOWN" "small" "large" "large" "small" "large" "large"
[17] "small" "small" "large" "UNKNOWN" "UNKNOWN" "small" "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 0 848 0 886 0 0 909 0 NA 0 722 750 0 594 961 0 0 966 NA NA 0 804
unique( duplicatedNumbers )
[1] 5 4 2 1 3
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 5 4 2 1 3
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 19
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 966
which.min( manyNumbersWithNA )
[1] 11
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 37
range( manyNumbersWithNA, na.rm = TRUE )
[1] 37 966
manyNumbersWithNA
[1] 429 342 848 83 886 484 312 909 470 NA 37 722 750 360 594 961 143 343 966 NA NA 318 804
sort( manyNumbersWithNA )
[1] 37 83 143 312 318 342 343 360 429 470 484 594 722 750 804 848 886 909 961 966
sort( manyNumbersWithNA, na.last = TRUE )
[1] 37 83 143 312 318 342 343 360 429 470 484 594 722 750 804 848 886 909 961 966 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 966 961 909 886 848 804 750 722 594 484 470 429 360 343 342 318 312 143 83 37 NA NA NA
manyNumbersWithNA[1:5]
[1] 429 342 848 83 886
order( manyNumbersWithNA[1:5] )
[1] 4 2 1 3 5
rank( manyNumbersWithNA[1:5] )
[1] 3 2 4 1 5
sort( mixedLetters )
[1] "A" "c" "g" "h" "H" "j" "N" "R" "s" "T"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 5.5 10.0 8.0 8.0 3.0 5.5 1.0 8.0 3.0 3.0
rank( manyDuplicates, ties.method = "min" )
[1] 5 10 7 7 2 5 1 7 2 2
rank( manyDuplicates, ties.method = "random" )
[1] 6 10 8 7 4 5 1 9 2 3
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 -0.12088993 1.80206698 0.01255969 0.68982832 -0.74279084 0.25990219 -1.10382097 -1.05037770
[14] 0.46509616 1.32102216
round( v, 0 )
[1] -1 0 0 0 1 0 2 0 1 -1 0 -1 -1 0 1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -0.1 1.8 0.0 0.7 -0.7 0.3 -1.1 -1.1 0.5 1.3
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -0.12 1.80 0.01 0.69 -0.74 0.26 -1.10 -1.05 0.47 1.32
floor( v )
[1] -1 -1 0 0 1 -1 1 0 0 -1 0 -2 -2 0 1
ceiling( v )
[1] -1 0 0 1 1 0 2 1 1 0 1 -1 -1 1 2
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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